Optimal Retail Return Policies with Wardrobing

Many retailers offer refunds to consumers who, after a trial period, return a product that they find does not fit their needs. Some consumers are willing to use this return option opportunistically for short‐term consumption rather than its intended purpose of resolving fit uncertainty. Such behavior has been termed “wardrobing.” Restocking fees (partial refunds) can be used to combat wardrobing. However, there is a trade‐off involved, since partial refunds will be viewed negatively by consumers who return an item due to a true lack of fit. In this study, we consider how the extent of wardrobing (how many consumers consider such behavior) and the benefit of wardrobing (how much value can be extracted during the trial) impact firm pricing decisions and profits in this retail context. Our results imply that an increase in the extent of wardrobing is most detrimental to profits when the current extent of wardrobing is low. On the contrary, if the extent of wardrobing is already very high, and the benefit of wardrobing to consumers is also high, the retailer can set prices and refunds such that additional wardrobing actually increases firm profits. In a model extension, we show how a retailer can effectively screen wardrobers from ordinary consumers by offering a menu of price/refund pairs, and that such an approach can lead to increased profits if the extent of wardrobing is sufficiently high. Overall, our findings provide new insights into how retailers can set prices and refund policies to effectively manage opportunistic behavior by consumers.     

On minimum <Emphasis Type="Italic">m</Emphasis>-connected <Emphasis Type="Italic">k</Emphasis>-dominating set problem in unit disc graphs

Minimum m-connected k-dominating set problem is as follows: Given a graph G=(V,E) and two natural numbers m and k, find a subset S⊆V of minimal size such that every vertex in V∖S is adjacent to at least k vertices in S and the induced graph of S is m-connected. In this paper we study this problem with unit disc graphs and small m, which is motivated by the design of fault-tolerant virtual backbone for wireless sensor networks. We propose two approximation algorithms with constant performance ratios for m≤2. We also discuss how to design approximation algorithms for the problem with arbitrarily large m. This work was supported in part by the Research Grants Council of Hong Kong under Grant No. CityU 1165/04E, the National Natural Science Foundation of China under Grant No. 70221001, 10531070 and 10771209.     

知识经济时代企业发展的思考

在知识经济时代 ,我国企业不可不惜代价强行模仿 ,而应在国家科教兴国战略下 ,结合我国企业长期以来发展的实践经验 ,利用知识经济时代的良好环境 ,对企业管理模式进行创新 ,做到既古为今用、洋为中用 ,又独树一帜     

基于Authorware软件的数学教学

本文将制作课件的两个教学软件Authorware与PowerPoint的交互性优势进行比较,对Authorware的交互性优势如何运用到数学教学中进行了讨论.     

游移的起点:无法栖居的启蒙主义心态——兼与刘再复先生讨论

中国新文化新文学起点的确立,是个急欲辨明却又几于无解的论题,其理由在于相关研究者对新文化新文学的认同、偏爱态度强烈,其间包含着难以自觉的启蒙主义心态,惟思想进步是举,由此,在理据上贬损现代文化、文学变动中传统话语里的异端因素,却又单取贵族文学的名号以标画传统文学的极致,甚至指认贵族精神的八字真言为中外文学的伟大所在.如此说法误会了文学与人生两界的基本分野,也遮蔽了中国支化、文学呈示异端、尽现物象的创生造化的诗学之途.     

中华学与中国古代史研究

中华学的创立，有助于从根本上消除封建正统史观的影响，建立新的古史体系；有助于从更大的时空范围研究中国古代史；有助于认识中华文明对世界的贡献；有助于推动中华史的研究     

国民塑造与传统德育的近代转型:以修身科的历史嬗变为中心

在中国社会的近代化转型中,传统道德教育受到前所未有的撼动,并因此出现了断裂,陷入困境。在此背景下,作为近代中国道德教育的主要载体——修身科应运而生。从臣民的教化到国民的培养,从个人私德的修炼到国民品性的完善,从传统的教化灌输到学生本位的课程教育,在修身科的这一历史嬗变中,传统德育的教学目标、内容及方式有了根本性的改变;但传统德育的近代转型却未彻底实现,因此在国民塑造上也仅是缺位的启蒙。     

Estimation and selection in linear mixed models with missing data under compound symmetric structure

It is quite appealing to extend existing theories in classical linear models to correlated responses where linear mixed-effects models are utilized and the dependency in the data is modeled by random effects. In the mixed modeling framework, missing values occur naturally due to dropouts or non-responses, which is frequently encountered when dealing with real data. Motivated by such problems, we aim to investigate the estimation and model selection performance in linear mixed models when missing data are present. Inspired by the property of the indicator function for missingness and its relation to missing rates, we propose an approach that records missingness in an indicator-based matrix and derive the likelihood-based estimators for all parameters involved in the linear mixed-effects models. Based on the proposed method for estimation, we explore the relationship between estimation and selection behavior over missing rates. Simulations and a real data application are conducted for illustrating the effectiveness of the proposed method in selecting the most appropriate model and in estimating parameters.